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Record W2129832190 · doi:10.1109/tvt.2007.897639

Blind Channel Estimation for Orthogonal STBC in MISO Systems

2007· article· en· W2129832190 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Vehicular Technology · 2007
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAlgorithmEstimatorChannel (broadcasting)MathematicsFadingMatrix decompositionBlock codeMIMOSpace–time block codeComputer scienceComputational complexity theoryDecoding methodsStatisticsTelecommunicationsEigenvalues and eigenvectors

Abstract

fetched live from OpenAlex

This paper presents a closed-form blind channel estimation scheme for orthogonal space-time block codes in multiple-input single-output (MISO) systems, with specific focus on Alamouti's code for two transmit antennas. The channel matrix is estimated from the eigenvalue decomposition of the fourth-order cumulant matrix of the received signal. Unlike previous blind estimation schemes for MISO systems, the proposed algorithm is tested with block and slowly fading channels. The proposed scheme performs very well in both cases. A single pilot tuple is required to correctly assign the estimated to the actual channels and to resolve the sign ambiguity common to all blind estimators. It is shown that this scheme outperforms the only other available blind channel estimation scheme for this scenario. To achieve good performance in terms of bit error rate, 100-300 sample points are sufficient to provide accurate channel estimates. The main disadvantage of the proposed scheme is the complexity associated with the estimation of fourth-order cumulants. This complexity is reduced by exploiting the symmetry inherent in the cumulant matrix.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.916
Threshold uncertainty score0.802

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.269
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it